Australian National University

A Theoretical Framework for Knowledge- Based Entity Resolution

Zusammenfassung

Entity resolution is concerned with deciding whether two representations of entities
refer to the same real-world object. It is one of the major impediments affecting data
quality provided by information systems. The difficulty of this problem has been
widely acknowledged by various research communities and industry practitioners.
State-of-the-art approaches to entity resolution mostly favor similaritybased methods.
In this talk, I will present a simple yet expressive framework that can support
knowledge-based entity resolution. Knowledge patterns, as the building blocks of the
framework, have the capability of capturing knowledge about different entities at an
arbitrary level of abstraction. From a logical point of view, the expressive power of
the framework is equivalent to a fragment of first-order logic including conjunction,
disjunction and a certain form of negation. Thus, the question of how efficiently
redundancy can be eliminated from knowledge patterns naturally arises. I will discuss
the containment problem of knowledge patterns and introduce a decision procedure
for determining containment and equivalence between knowledge patterns. It turns
out that the containment problem of knowledge patterns is NP-complete w.r.t.
expression complexity but in PTIME w.r.t. data complexity. Finally, I will introduce a
mechanism of optimizing knowledge patterns, which can lead to more efficient
knowledge management and thus improve accuracy of entity resolution over time

Vortragender

Dr. Qing Wang completed her Ph.D. in Computer Science at Christian-Albrechts-
University Kiel, Germany, in 2010. She has over a decade of industry experience, and
has led and contributed to many IT system projects in the past. From 2009 to 2012,
she also worked as a Systems Analyst and a Research Fellow at the University of
Otago, New Zealand. In April 2012, she joined the Research School of Computer
Science, The Australian National University, Australia. Her research interests are in
the areas of database theory and applications, knowledge representation and
reasoning, conceptual modelling and formal methods.